Mainz 2017 – wissenschaftliches Programm

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Q: Fachverband Quantenoptik und Photonik

Q 4: Quantum Optics I

Q 4.6: Vortrag

Montag, 6. März 2017, 16:00–16:15, P 5

A Kalman Filter Approach to Quantum State Reconstruction — •Karsten Bölts, Stefan Scheel, and Boris Hage — Institut für Physik, Universität Rostock, Albert-Einstein-Str. 23-24, 18059 Rostock, Deutschland

Kalman filtering, a technique which is mostly used for dynamical state estimation in the field of engineering, can also be applied to quantum state reconstruction [1]. This method yields not only the optimal Bayesian state estimate but also treats the measurement uncertainties properly and can in principle be adapted to any tomographic set-up. The reconstruction scheme is mainly based on linear vector equations and hence it is well suited for hardware implementation.

Here we show how to apply the Kalman filter method to balanced homodyne tomography [2]. We implemented a version of the algorithm on a field programmable gate array (FPGA) to enable hardware-assisted real-time state reconstruction and calculation of error bars.

[1] K. M. R. Audenaert and S. Scheel, New J. Phys. 11, 023028 (2009)

[2] E. Agudelo, J. Sperling, W. Vogel, S. Köhnke, M. Mraz and B. Hage, Phys. Rev. A 92, 033837 (2015)